Order evaluation system for use in a healthcare location

ABSTRACT

An order evaluation system for use in a healthcare location evaluates an order against a first set of patient assessment data elements to determine whether the order should be issued. If the order is issued, a rules generator generates a patient-specific rule that is consistent with the order. The patient-specific rule is continuously applied to a second set of patient assessment data to determine whether the rule has been contravened. If the rule is contravened, an alert is issued. An alert may direct changes in, or cancellation of, an order.

RELATIONSHIP TO OTHER APPLICATIONS

This application is a continuation in part of application Ser. No.10/654,668 filed Sept. 4, 2003 and a continuation in part of applicationSer. No. 10/946,548 filed Sept. 21, 2004 now U.S. Pat. No. 7,256,708,both of which are continuations-in-part of application Ser. No.09/443,072 filed Nov. 18, 1999, now U.S. Pat. No. 6,804,656 issued Oct.12, 2004, which claims the benefit of U.S. Provisional Application No.60/141,520, filed Jun. 23, 1999. The Ser. No. 10/654,668, 10/946,548,09/443,072, and the 60/141,520 applications are hereby incorporated byreference in their entirety for all purposes.

BACKGROUND

Embodiments of this invention relate generally to providing care topatients in healthcare locations. More particularly, embodiments of thisinvention provide a system and method for evaluating orders forprocedures, tests, and medication against patient-related data and tochallenge orders that are contraindicated by those data.

Advances in communications, video displays, monitoring devices andcomputers have made it possible to remotely monitor hundreds ofmonitored patients. Alerting systems may be deployed to alert healthcareproviders when certain conditions are met. For example, in U.S. Pat. No.5,942,986 issued to Shabot, et. al for a “System And Method ForAutomatic Critical Event Notification,” describes a critical eventnotification system that permits review of a patient's diagnosticinformation, lab results, chart, or other data, automatically, bycomputer or similar equipment, and it provides for automatic paging of aresponsible physician or physicians should a “critical event” bedetected. The decision to page an individual is made automatically bythe system, and does not require a direct human decision.

“Decision Support Systems in Critical Care” (Edited by M. Michael Shabotand Reed M. Gardner, 1994), is a compilation of articles thatcollectively describe the application of computers in health caresettings. Decision support systems are defined as systems that receivemedical data as input and produce medical information and/or knowledgeas output. In some implementations, decision support systems utilizeinferencing methods to detect associations between different pieces ofinformation, alerting clinicians to certain patterns of events, whichmay be serious or life-threatening.

An example implementation of an inferencing method is described in thecontext of analyzing blood gas readings and laboratory results. Threedifferent types of alerting algorithms are described: 1) high and lowcritical values 2) calculation-adjusted critical values, and 3) criticaltrends. (See, Decision Support Systems in Critical Care, pages 157-65.)The calculation-adjusted critical value algorithm reflects thedependence of the algorithm on multiple parameters. The application ofthe inferencing module produces an alert that is displayed on a screenor sent to a wireless device.

In U.S. Pat. No. 6,804,656 issued to Applicants, a smart alarm systemwas described. The smart alarm system of the '656 Patent, constantlymonitors physiologic data and all other clinical information stored inthe database (labs, medications, etc). The rules engine searches forpatterns of data indicative of clinical deterioration. By way ofillustration, one family of alarms looks for changes in vital signs overtime, using pre-configured thresholds. These thresholds (also referredto as “rules”) are patient-specific and setting/disease-specific.Physiologic alarms can be based on multiple variables. For example, onealarm looks for a simultaneous increase in heart rate of 25% and adecrease in blood pressure of 20%, occurring over a time interval of 2hours. Alarms also track additional clinical data in the patientdatabase. Other rules follow laboratory data (e.g. looking for need toexclude active bleeding and possibly to administer blood). Regardless ofthe data elements that are used, the purpose of the rules is tofacilitate detection of changes in a patient's condition (whether thatcondition is improving or degrading) in a predictive manner and toautomate a response appropriate to the “new” condition.

Systems have also been developed that check orders for medicationagainst patient records to identify possible drug interactions and drugallergies. While these systems have proven useful in protecting thehealth of patients, it would be desirable to evaluate orders formedications, procedures, and tests against patient information and tocreate rules for patients that are consistent with orders directed tothat patient.

SUMMARY

An embodiment of the present invention evaluates an order against afirst set of patient assessment data elements to determine whether theorder should be issued. If the order is issued, a rules generatorgenerates a patient-specific rule that is consistent with the order. Thepatient-specific rule is continuously applied to a second set of patientassessment data to determine whether the rule has been contravened. Ifthe rule is contravened, an alert is issued.

As used herein, a healthcare location may be a remote clinic, a doctor'soffice, a field hospital, a disaster aid station, a patient transportvehicle and similar care facilities. A patient may be selected formonitoring based on criteria established by the treatment facility. Byway of illustration and not as a limitation, a “monitored patient”comprises a critically ill patient, an acutely ill patient, a patientwith a specific illness, a patient with serious injuries, a surgicalpatient and a patient with an uncertain diagnosis.

In another embodiment of the present invention, order writing softwarefacilitates the ordering of procedures and medications usingpatient-specific data. The order writing software and the continued caresoftware are interactive allowing a caregiver to access features of bothapplications simultaneously, so that patient orders are given that areconsistent and not conflicting with a patient's status and condition(i.e., allergies to medications or medications that may conflict withthe order in question).

Patient monitoring equipment acquires monitored data elements from apatient monitoring station and transmits the monitored data (sometimesalso referred to herein as, “monitoring data”) over a network to aremote command center. Monitored data comprises physiological dataelements, video data elements, and audio data elements. The remotecommand center receives the monitored data from all patient monitoringstations. The remote command center also accesses other data relating tothe condition of a patient. By way of illustration and not aslimitation, the remote command center has access to data relating topersonal information about the patient (name, address, marital status,age, gender, ethnicity, next of kin), medical history (illnesses,injuries, surgeries, allergies, medications), admissions information(symptoms, physiological data, time of admission, observations ofadmitting caregiver), treatment, lab data, test reports (radiologyreports and microbiology reports for example), physician's notes, apatient's diagnosis, prescriptions, history, condition, laboratoryresults and other health-relevant data (collectively “patient data”) tothe extent available from the healthcare location. The data available tothe remote command center over the network, that is, the monitored dataand the patient data, is collectively referred to as “assessment data.”

A rules engine applies a rule or rule set to the data elements selectedfrom the assessment data from each monitored patient to determinewhether the rule for that site has been contravened. In the event therule has been contravened, an alert at the remote command center istriggered. Rules for each monitored patient may be established andchanged at the remote command center for each as the patients'conditions warrant. In one embodiment of the present invention, a ruleis established to determine whether a patient's condition isdeteriorating. In another embodiment, a rule is established to determinewhether a patient's condition is improving. In yet another embodiment ofthe present invention, an alert that a rule has been contravenedcomprises advice on treatment of the patient.

A patient rules generator establishes one or more rules for themonitored patient associated with a patient monitoring station. The ruleis consistent with orders issued with respect to the patient. In anembodiment of the present invention, the patient rules generatorcollects rules performance measures indicative of the ability of therule to predict changes in the condition of a patient and uses thesemeasures to assess the efficacy of the rule. The patient rules generatormay update a rule, determine that a rule is acceptable as is, ordetermine that there is insufficient data to revise a rule.

The patient rules generator may also evaluate the assessment data ofpatients with similar conditions to determine whether a predictive rulecan be written and applied to patients with the same or similarconditions. The patient rules generator may also test a proposed ruleagainst historical data to determine whether the rule is predictive of achange in a patient's condition.

In yet another embodiment of the present invention, the patient rulesgenerator generates a rule that is consistent with the service levelmeasures established by a site assessment module.

Another embodiment of the present invention provides continued caresoftware that uses elements of the assessment data to provide decisionsupport and that prompts a user for input to provide decision support tocaregivers. A decision support algorithm responds to elements ofassessment data to produce textural material describing a medicalcondition, scientific treatments and possible complications. Thisinformation is available in real time to assist in all types of clinicaldecisions from diagnosis to treatment to triage.

In an embodiment of the present invention, a healthcare location patientcare system provides care to healthcare location patients based on thecapabilities of the healthcare location. In this embodiment, the rulesengine, the decision support algorithms, the order writing softwarefacilities, and the continued care software are adapted to thecapabilities of the healthcare location based on the application of siteassessment rules to the healthcare location. In another embodiment ofthe present invention, components of a healthcare location patient caresystem may be supplied to the healthcare location to improve the levelof its treatment capabilities. In still another embodiment of thepresent invention, components of the healthcare location are packagedand assigned a site assessment code. The code is used by the remotecommand center to predetermine elements of the site assessment processthereby simplifying that process.

In another embodiment of the present invention, patient monitoringequipment acquires monitored data elements from a patient monitoringstation and stores monitoring data locally. The stored monitoring datais sent to a remote command center along with patient data at apre-established time or when requested by remote command center. Theremote command center evaluates the “delay” monitored data andassessment data in the same mariner as if these data were received inreal time. By way of illustration, the remote command center will applythe rules engine and the decision support algorithms to the delayedmonitored data and patient data and provide guidance to the healthcarelocation. This embodiment of the present invention thus provides highquality care in environments where continuous high bandwidthcommunications are not available or economically infeasible.

In still another embodiment of the present invention, the delivery ofstored monitoring data and patient data is expedited by an urgentconsultation warning system (herein, the UCWS). The UCWS constantlyevaluates the monitoring data and patient data before those data arestored to determine if an urgent consultation is warranted. By way ofillustration and not as a limitation, changes in hemodynamic andrespiratory measures over time indicative of a degrading condition of apatient would trigger an immediate reporting of all stored monitored andpatient data to the remote command center for evaluation.

It is therefore an aspect of the present invention to evaluate an orderagainst a first set of patient assessment data elements to determinewhether the order should be issued.

It is another aspect of the present invention to create a rule for apatient that is consistent with the orders issued for that patient.

It is yet another aspect of the present invention to provide thedecision support system, the rules generator and the rules engine withina command center that is remote from the healthcare location where thepatient is located.

It is yet another aspect of the present invention to establish and/orrevise rules at the remote command center and to apply a rules engine to“assessment data” to determine whether a rule is contravened.

It is another aspect of the present invention to determine based onassessment data whether the condition of a monitored patient warrantsrevising an order.

It is still another aspect of the present invention to issue an alertfrom the remote command center in the event a rule is contravened.

It is an aspect of the present invention to provide treatmentinformation in an order for an intervention issued by the remote commandcenter to a treatment facility where a monitored patient is receivingcare.

It is a further aspect of the present invention to apply decisionsupport algorithms to data relating to the condition of a patient toprovide decision support to caregivers.

It is another aspect of the present invention to provide a videovisitation system that allows a remote visitation participant toparticipate in a video/audio conferencing session with a patient and/ora local visitation participant.

It is yet another aspect of the present invention to periodicallyacquire rules performance measures and use those measures to assess theefficaciousness of a rule.

In an embodiment of the present invention, an order evaluation systemcomprises a network, a datastore accessible via the network, a decisionsupport system connected to the network, a rules generator connected tothe network, and a rules engine connected to the network. The datastorecomprises assessment data elements indicative of a medical conditionassociated with a patient.

The decision support system comprises an order checking module that isadapted for receiving an order; evaluating the order using a first setof selected assessment data elements; challenging the order if the orderis contraindicated by the first set of selected assessment dataelements; and sending the order to an order writing module if the orderis indicated by the first set of selected assessment data elements.

The rules generator is adapted for establishing a patient-specific ruleconsistent with the order. In an embodiment of the present invention,the patient specific rule is applied continuously. In another embodimentof the present invention, the patient specific rule for the patientcomprises an algorithm. The rules engine is adapted for applying thepatient specific rule to a second set of selected assessment dataelements; determining whether the patient-specific rule for the patienthas been contravened; and issuing an alert if the patient-specific rulefor the patient has been contravened. In an embodiment of the presentinvention, the alert comprises an instruction to review the order. Inyet another embodiment of the present invention, the alert comprises apatient intervention protocol and order.

In another embodiment of the present invention, the decision supportsystem, the rules generator and rules engine are located within acommand center and wherein the patient is located that is remote fromthe command center. In this embodiment, the command center is adaptedfor monitoring a plurality of patients in a plurality of geographicallydispersed health cared locations 24 hours per day 7 days per week.

In an embodiment of the present invention, the order is an order formedication and the first set of selected assessment data is selectedfrom the group consisting patient data, medication data, clinical data,monitored data, physiological data, and symptomatic data. By way ofillustration and not as a limitation, in another embodiment, themedication data comprises current medications and drug allergyinformation. In yet another embodiment of the present invention, thephysiological data comprises data indicative of liver function and renalfunction.

In an embodiment of the present invention, the order is an order for aprocedure and the first set of selected assessment data is selected fromthe group consisting of patient data, medication data, clinical data,monitored data, physiological data, and symptomatic data. By way ofillustration and not as a limitation, in another embodiment, themedication data comprises current medications and drug allergyinformation.

In various embodiments of the present invention, the second set ofselected data elements comprise: a physiological data element of thepatient and a clinical data element of the patient; a physiological dataelement of the patient and a medication data element of the patient; aphysiological data element of the patient and a laboratory data elementof the patient; a clinical data element of the patient and a laboratorydata element of the patient; and a physiological data element of thepatient and another physiological data element of the patient.

In another embodiment of the present invention, the second set ofselected data elements comprise at least two data elements of thepatient selected from the group consisting of a physiological dataelement, a clinical data element of the patient, a medication dataelement of the patient, and a laboratory data element of the patient.

DESCRIPTION OF THE FIGURES

FIG. 1 illustrates a block diagram of the components of a monitoredpatient care system according to embodiments of the present invention.

FIG. 2 illustrates the components of a transportable patient care unitaccording to embodiments of the present invention.

FIG. 3 illustrates a display and control system according to anembodiment of the present invention.

FIG. 4 illustrates a decision support system according to an embodimentof the present invention.

FIG. 5 illustrates an order writing data flow according to an embodimentof the present invention.

FIGS. 6A, B, C, and 6D illustrate the flow of a decision supportalgorithm for acalculous cholecsystitis according to an embodiment ofthe present invention.

DETAILED DESCRIPTION

The following terms used in the description that follows. Thedefinitions are provided for clarity of understanding:

-   assessment data—assessment data is all data relevant to the health    of a patient.-   healthcare location—A “healthcare location;” a facility, whether    temporary or permanent, that is not generally equipped to provide    expert medical care on a twenty-four basis. By way of illustration    and not as a limitation, a healthcare location may be a remote    clinic, a doctor's office, a field hospital, a disaster aid station,    a patient transport vehicle and similar care facilities-   caregiver—an individual providing care to a patient. Examples    include a nurse, a doctor, medical specialist (for example and    without limitation an intensivist, cardiologist or other similar    medical specialist).-   clinical data—data relating to the observed symptoms of a medical    condition.-   monitored patient—a person admitted to a healthcare location.-   monitored data—data received from monitoring devices connected to a    monitored patient.-   monitored patient—a monitored patient from whom monitored data is    collected and whose condition is subject to continuous real-time    assessment from a remote command center.-   patient data—data relating to a patient's diagnosis, prescriptions,    history, condition, laboratory results and other health-relevant    data.-   physiological data—any data relating to the functions of the human    body and its processes.-   symptom—any sign or indication of a health condition that can be    identified from patient reports and/or assessment data.

An embodiment of the present invention evaluates an order against afirst set of patient assessment data elements to determine whether theorder should be issued. If the order is issued, a rules generatorgenerates a patient-specific rule that is consistent with the order. Thepatient-specific rule is continuously applied to a second set of patientassessment data to determine whether the rule has been contravened. Ifthe rule is contravened, an alert is issued.

As used herein, a healthcare location may be a remote clinic, a doctor'soffice, a field hospital, a disaster aid station, a patient transportvehicle and similar care facilities. A patient may be selected formonitoring based on criteria established by the treatment facility. Byway of illustration and not as a limitation, a “monitored patient”comprises a critically ill patient, an acutely ill patient, a patientwith a specific illness, a patient with serious injuries, and a patientwith an uncertain diagnosis.

In another embodiment of the present invention, order writing softwarefacilitates the ordering of procedures and medications usingpatient-specific data. The order writing software and the continued caresoftware are interactive allowing a caregiver to access features of bothapplications simultaneously, so that patient orders are given that areconsistent and not conflicting with a patient's status and condition(i.e., allergies to medications or medications that may conflict withthe order in question).

Patient monitoring equipment acquires monitored data elements from apatient monitoring station and transmits the monitoring data over anetwork to a remote command center. Monitored data comprisesphysiological data elements, video data elements, and audio dataelements. The remote command center receives the monitoring data fromall patient monitoring stations. The remote command center also accessesother data relating to the condition of a patient. By way ofillustration and not as limitation, the remote command center has accessto data relating to personal information about the patient (name,address, marital status, age, gender, ethnicity, next of kin), medicalhistory (illnesses, injuries, surgeries, allergies, medications),admissions information (symptoms, physiological data, time of admission,observations of admitting caregiver), treatment, lab data, test reports(radiology reports and microbiology reports for example), physician'snotes, a patient's diagnosis, prescriptions, history, condition,laboratory results and other health-relevant data (collectively “patientdata”) to the extent available from the healthcare location. The dataavailable to the remote command center over the network, that is, themonitoring data and the patient data, is collectively referred to as“assessment data.”

In an embodiment of the present invention, a monitored patient caresystem provides care to monitored patients based on the capabilities ofthe healthcare location. In this embodiment, the rules engine, thedecision support algorithms, the order writing software facilities, andthe continued care software are adapted to the capabilities of thehealthcare location based on the application of site assessment rules tothe healthcare location. In another embodiment of the present invention,components of a healthcare location patient care system may be suppliedto the healthcare location to improve the level of its treatmentcapabilities. In still another embodiment of the present invention,components of the healthcare location are packaged and assigned a siteassessment code. The code is used by the remote command center topredetermine elements of the site assessment process thereby simplifyingthat process.

FIG. 1 illustrates a block diagram of the components of a monitoredpatient care system according to embodiments of the present invention. Amonitored patient care system 100 comprises patient monitoring station“A” 105. While FIG. 1 illustrates a single patient monitoring station,the invention is not so limited. Multiple patient monitoring stationsmay be used without departing from the scope of the present invention.For the sake of clarity, the description that follows will refer topatient monitoring station “A” 105. However, the description applies toall patient monitoring stations within the monitored patient care system100.

Patient monitoring station “A” 105 comprises a general purpose computer110, a patient monitoring device 115, a camera 120, and a duplex audiosystem 125. While FIG. 1 illustrates a patient monitoring device, theinvention is not so limited. Multiple patient monitoring devices may beused without departing from the scope of the present invention. For thesake of clarity, the description that follows will refer to patientmonitoring 115.

General purpose computer 110 provides data entry, display and printingcapabilities through means known to those skilled in the art.

As will be appreciated by those skilled in the art, monitoring station“A” 105 may be portable without departing from the scope of the presentinvention. In an embodiment of the present invention, monitoring station“A” 105 is integrated into a patient supporting device, as for exampleand not as a limitation, a bed, a gurney, or a wheelchair. Monitoringstation “A” 105 may also be assembled on a cart or other mobilestructure.

The components of patient monitoring station “A” 105 are connected tonetwork 145 via network interface 140. Network 145 may be a wirednetwork, a wireless network, a satellite network, a public switchedtelephone network, an IP network, a packet switched network, a cellphone network, a cable network, and a coax network, a hybrid fiber coaxnetwork.

Pharmacological supplies 180 comprise an inventory of medicines that isprovided to a healthcare location depending on circumstances. By way ofillustration and not as a limitation, a monitored patient care system100 may be operated in a full service hospital facility or droppedshipped to a disaster area where the primary concern is sanitation-basedillnesses. In the former instance, the full service hospital would haveaccess to all available medications. However, in the case of the dropshipped field hospital, pharmacological supplies 180 would comprisethose medications, diagnostic tools, and preventive agents that areuseful in countering the expected diseases and not readily available tothe healthcare location. In contrast, if the disaster area is mostlikely to experience patients with physical injuries, pharmacologicalsupplies would be weighted to supplies needed to diagnose, treat, andcomfort the wounded.

An optional site assessment module 130 and an optional patientassessment module 135 connect to network interface 140 via generalpurpose computer 110. It is anticipated that a monitored patient caresystem 100 equipped with the optional site assessment module 130 and theoptional patient assessment module 135 will be used in healthcarelocations that have limited resources. Site assessment module 130provides information indicative of the ability of a healthcare locationto provide diagnostic, laboratory, surgical, and pharmacologicalservices. In an embodiment of the present invention, the site assessmentmodule acquires data from the healthcare location produces service levelmeasures comprising an inventory of available monitoring data elements,an inventory of available diagnostic services, an inventory of availablesurgical treatment services, and an inventory of available laboratoryservices. These data may be acquired via a survey or by reference to adatabase in which the survey data of the healthcare location are stored.Alternatively, in another embodiment of the present invention, amonitored patient care system comprises an assessment code that detailsthe capability of the monitored patient care system 100. By way ofillustration and not as a limitation, the assessment code may indicatethe number of monitoring devices incorporated into the monitored patientcare system 100, the patient parameters that can be acquired using themonitoring devices, and the pharmacological supplies 180 provided withthe monitored patient care system 100.

Optional patient assessment module 135 provides patient condition dataindicative of a monitored patient to remote command center 150. In anembodiment of the present invention, patient assessment module 135acquires data relating to a patient's diagnosis, prescriptions, history,condition, laboratory results and other health-relevant data. These datamay be acquired via a survey or by reference to a database in which thepatient condition data are stored.

As will appreciated by those skilled in the art, site assessment module130 and a patient assessment module 135 may be standalone components ormay be software applications operating on general purpose computer 110.

Also connected to network 145 is remote command center 150. Remotecommand center 150 comprises a patient rules generator 155, a rulesengine 160, decision support system 155, display and control system 165,and audio/video (A/V) conferencing server 170. Decision support system158 issues instructions to the rules generator 155 when rules requiredfor a patient. Once the rules are generated by rules generator 155, thedecision support system 158 causes the rule to be referred to the rulesengine 160 for subsequent application to the specific patient for whomthe rule was originally generated. A network interface 175 providesconnectivity between network 145 and the other elements of the remotecommand center. Network 145 is configured to permit access to externalnetworks (not illustrated), such as the Internet.

Video camera 120 is movable both horizontally and vertically andzoomable through remote commands from the display and control system 165of remote command center 150 so that specific views of the patient maybe obtained both up close and generally. Duplex audio system 125comprises a speaker and microphone (not illustrated) to permit bothone-way audio monitoring of the patient and two-way communication withthe patient or others in proximity to patient monitoring station “A”105.

Patient monitoring device 115 acquires physiological data from a patientin real-time. In an embodiment of the present invention, general purposecomputer 110 comprises a printer that receives and prints orders andinstructions from an authorized remote caregiver. By way of illustrationand not as a limitation, an order comprises a lab order, a medication,and a procedure. Orders are tailored to the capabilities of thehealthcare location patient care system 100.

A network interface 140 provides access to network 145 for transmissionof the monitored data, video signal, and audio signals to the remotecommand center 125 and the receipt of the audio signals and, optionally,printer signals at the monitoring station.

FIG. 2 illustrates the components of a transportable patient care unitaccording to embodiments of the present invention. A transportablepatient care unit 200 comprises the components illustrated in FIG. 1mounted on a cart 250. Video camera 205 is movable both horizontally andvertically and zoomable through remote commands from the display andcontrol system 165 of remote command center 150 (see, FIG. 1) so thatspecific views of the patient may be obtained both up close andgenerally. A microphone 210 and a speaker 215 permit both one-way audiomonitoring of the patient and two-way communication with the patient orothers located in proximity to transportable patient care unit 200.Patient monitoring devices 220A-220D acquire physiological data from apatient in real-time. A printer 230 receives and print orders from anauthorized caregiver. By way of illustration and not as a limitation, anorder comprises a lab order, a medication, and a procedure. A networkinterface 255 provides access to a network (see FIG. 1, 150) fortransmission of the monitored data, video signal, and audio signals to aremote command center and the receipt of the audio signals and printersignals at the monitoring station. A general purpose computer 210 allowson site care givers to provide additional data that may be germane tothe care of the patient.

Referring again to FIG. 1, the remote command center 125 receivesmonitored data from patient monitoring station “A” 105 and patientcondition data from patient assessment module 135 via network 145through network interface 175. Monitored data comprises real-time datareceived from monitoring equipment at patient monitoring station “A” 105that is configured to receive physiological data monitored patient andassociated with patient monitoring station “A” 105.

The rules generator 155 and the rules engine 160 facilitate detection ofimpending problems and automate problem detection thereby allowing forintervention before a patient condition reaches a crisis state. Rulesengine generator 155 establishes one or more rules for the monitoredpatient associated with patient monitoring station “A” 105. In anembodiment of the present invention, rules generator 155 generates arule that is consistent with the patient assessment data and with theservice level measures established by the site assessment module 130.The rules engine 160 continuously applies a rule to selected dataelements of patient assessment data (assessment data is all datarelevant to the health of a patient) to determine whether the rule for amonitored patient has been contravened. In the event the rule has beencontravened, the remote command center issues an alert.

In one embodiment of the present invention, a rule is established todetermine whether a patient's condition is deteriorating and an alertcomprises an intervention order and protocol. In another embodiment ofthe present invention, the rules engine is further adapted to determinewhether a monitored patient requires monitoring by a monitoring station.If not, a release protocol and order are issued. In still anotherembodiment of the present invention, a rule dictates threshold limitsfor changes over time of specific vital sign data. Thresholds that arepatient-specific disease-specific are established. The rules engine thenevaluates the monitored data for the specific vital sign data todetermine if a change threshold has been exceeded.

For example, a patient with coronary artery disease can developmyocardial ischemia with relatively minor increases in heart rate. Heartrate thresholds for patients with active ischemia (e.g. those withunstable angina in a coronary care unit) are set to detect an absoluteheart rate of 75 beats per minute. In contrast, patients with a historyof coronary artery disease in a surgical ICU have thresholds set todetect either an absolute heart rate of 95 beats per minute or a 20%increase in heart rate over the baseline. For this threshold, currentheart rate, calculated each minute based on the median value over thepreceding 5 minutes, is compared each minute to the baseline value (themedian value over the preceding 4 hours).

In another embodiment of the present invention, a rule is based onmultiple variables. By way of illustration, a rule is contravened if therules engine determines that monitored data reflects both a simultaneousincrease in heart rate of 25% and a decrease in blood pressure of 20%,occurring over a time interval of 2 hours.

For multi-variable rules, thresholds rely on known or learnedassociations between changes in multiple variables, which variables maycomprise diverse data types. Thus, a rule may associate monitoredphysiological data with patient clinical data. The association maychange depending on the diagnosis of the patient, the medication giventhe patient, and the results of laboratory data. For example, a rule mayassociate central venous pressure and urine output, because simultaneousdecreases in these two variables can indicate that a patient isdeveloping hypovolemia. Another rule may cause the rules engine toevaluate laboratory data (e.g. looking for need to exclude activebleeding and possibly to administer blood).

In an embodiment of the present invention, a rule established for amonitored patient and the monitored patient is associated with aparticular monitoring station. In this embodiment, if the patient werelater associated with a different monitoring station, the remote commandcenter would associate the rule with the different monitoring station atthe time that the association between the monitored patient and thedifferent monitoring station is made. In this way, rules “move” with thepatient without manual intervention.

In another embodiment of the present invention, patient rules generator155 establishes one or more rules for the monitored patient associatedwith patient monitoring station “A” 105. The patient rules generator 155receives rules performance measures indicative of the ability of therule to predict changes in the condition of a patient and uses thesemeasures to assess the efficacy of the rule. By way of illustration andnot as a limitation, the rules performance measures may be derived fromsurvey data from healthcare professionals with experience with the ruleor with the relationship of certain variables used by the rule to othervariables or to a particular medical condition. Alternatively or inconjunction with survey data, the patient rules generator 155 may reviewhistorical data using multivariate analyses to relate variables, rules,and patient outcomes. By way of illustration and not as a limitation,the patient rules generator 155 may use ANOVA or BSS to automaticallyproduce rules performance measures of existing rules and to identify newrelationships among variables that may be used to form new rules. Thepatient rules generator 155 may update a rule, determine that a rule isacceptable as is, or determine that there is insufficient data to revisea rule.

The patient rules generator 155 may also evaluate the assessment data ofpatients with similar conditions to determine whether a predictive rulecan be written and applied to patients with the same or similarconditions. The rules generator 155 may also test a proposed ruleagainst historical data to determine whether the rule is predictive of achange in a patient's condition.

In yet another embodiment of the present invention, the patient rulesgenerator 155 generates a rule that is consistent with the service levelmeasures established by a site assessment module 130.

In another embodiment of the present invention, patient monitoringequipment acquires monitored data elements from a patient monitoringstation and stores monitoring data in general purpose computer 110. Thestored monitoring data is sent from general purpose computer 110 to theremote command center 150 along with patient data under control of anoptional communications scheduler 112 at a pre-established time such ashour or when an “event” occurs as noted below, or when requested byremote command center 150. The remote command center 150 evaluates the“delayed” monitored data and assessment data in the same manner as ifthese data were received in real time. By way of illustration, theremote command center will generate rules using patient rules generator155, apply those rules using rules engine 160 to the delayed monitoreddata and patient data and provide guidance to the monitored patient caresystem 100. The decision support algorithms of decision support system158 may also be applied to the delayed monitored data and patient data.This embodiment of the present invention thus provides high quality carein environments where continuous high bandwidth communications are notavailable or economically infeasible.

In still another embodiment of the present invention, the delivery ofstored monitoring data and patient data is expedited by an urgentconsultation warning system (herein, the UCWS) operated by generalpurpose computer 110. The UCWS constantly evaluates the monitoring dataand patient data before those data are stored to determine if an eventhas occurred that warrants an urgent consultation. By way ofillustration and not as a limitation, changes in hemodynamic andrespiratory measures over time indicative of a degrading condition of apatient would trigger an immediate reporting of all stored monitored andpatient data to the remote command center 150 for evaluation.

Referring to FIG. 1, the display and control system 165 provides thehuman interface for the remote command center. FIG. 3 illustrates adisplay and control system according to an embodiment of the presentinvention. A display and control system 165 comprises a video displayunit 305, a computer terminal 310, a camera control 315, and an audiocontrol 320. The video display unit 305 displays real-time monitoringdata and video images from patient monitoring station “A” 105. Thecomputer terminal 310 allows selecting the layout and content displayedon the video display unit 305, provides access to the record of thepatient associated with patient monitoring station “A” 105, and permitsentry of data into that record. The camera control 315 permits controlfrom the remote command center 125 of the video camera 120 (see FIG. 1)at the patient monitoring station “A” 105. The audio control permitscontrol from the remote command center 150 of a microphone and a speakerwithin the duplex audio system 125 of patient monitoring station “A”105. Connectivity between the components of the display and controlsystems 165 and patient monitoring station “A” 105 is provided bynetwork interface 175, network 145, and network interface 140.

Referring again to FIG. 1, the remote command center 150 comprisesdecision support system 158. FIG. 4 illustrates a decision supportsystem according to an embodiment of the present invention. Referring toFIG. 4, decision support system 158 is connected to network interface175 and comprises a computer 405. Computer 405 operates continued caresoftware 420 and order writing software 415. Continued care software 410and order writing software 415 make calls to datastore 425 to access theassessment data related to a particular monitored patient associatedwith patient monitoring station “A” 105 (see, FIG. 1).

Continued care software 420 comprises decision support algorithms thatoperate on elements of assessment data and/or input from a caregiver tofacilitate decisions relating to diagnosis, treatment and triage.Continued care software may be applied at the time the patient isadmitted and throughout the patient's stay within a treatment facility.Thus, a diagnosis may be made based on the initial data acquired duringadmission, following the completion of laboratory procedures, or afterother pertinent information is acquired. In an embodiment of the presentinvention, continued care software 420 evaluates selected data elementsof assessment data continuously and provides an alert if those data areindicative of a different diagnosis. The alert may take the form ofsuggested diagnoses that are vetted by a series of questions posed bythe continued care software 420 to a caregiver. Based on the responsesto the questions, a suggested diagnosis may be eliminated. The alert mayalso comprise instructions for specific tests to be run on the monitoredpatient to help formulate a new diagnosis. Once a diagnosis isconfirmed, the continued care software 420 continues to monitor changesin patient data and issues an alert if the current diagnosis should bereevaluated by a caregiver.

Decision support system 158 also issues instructions to the rulesgenerator 155 when rules required for a patient. Once the rules aregenerated by rules generator 155, the decision support system 158 causesthe rule to be referred to the rules engine 160 for subsequentapplication to the specific patient for whom the rule was originallygenerated.

In another embodiment of the present invention, patient monitoringequipment acquires monitored data elements from a patient monitoringstation and stores monitoring data in general purpose computer 110. Thestored monitoring data is sent from general purpose computer 110 to theremote command center 150 along with patient data under control of anoptional communications scheduler 112 at a pre-established time such ashour or when an “event” occurs as noted below, or when requested byremote command center 150. The continued care decision support system158 evaluates selected data elements of the assessment data in the samemanner as if these data were received in real time and provides an alertif those data are indicative of a different diagnosis.

In still another embodiment of the present invention, the delivery ofstored monitoring data and patient data is expedited by an urgentconsultation warning system (herein, the UCWS) operated by generalpurpose computer 110. The UCWS constantly evaluates the monitoring dataand patient data before those data are stored to determine if an eventhas occurred that warrants an urgent consultation. By way ofillustration and not as a limitation, changes in hemodynamic andrespiratory measures over time indicative of a degrading condition of apatient would trigger an immediate reporting of all stored monitored andpatient data to the decision support system 158 for evaluation.

In still another embodiment of the present invention, continued caresoftware 420 operates on a diagnosis to “triage” a patient. For exampleand without limitation a caregiver requests an Apache II score based onthe diagnosis. Continued care software 420 calls selected data elementsfrom datastore 425 appropriate to the diagnosis. The values of theselected data elements are weighted according to an algorithm and apatient severity score is determined. This patient severity score isused to determine whether the patient is treated in a patient monitoringstation. For example, if one embodiment of the present invention, if theseverity score is greater than or equal to a particular threshold, thepatient is identified as requiring observation via a patient monitoringstation. If the severity score is less than that threshold, the patientis triaged to a facility other than a patient monitoring station,thereby assigning patient monitoring stations to patients who are mostlikely to benefit from monitoring and continued assessment.

Other scoring algorithms may be used without departing from the scope ofthe present invention. By way of illustration and not as a limitation,continued care software 420 may comprise algorithms to perform APACHEII, APACHE III, a history of present illness (HPI) score, a review ofsystems (ROS) score, a past, family, and/or social history (PFSH) score,and a mortality prediction model (MPM) score. The scoring results fromone or more of these algorithms may be used to determine a treatmentplan for the patient. As will be appreciated by those skilled in theart, a scoring result may be used to determine to apply resources to apatient that is determined to be a candidate for treatment consistentwith the patient's medical condition or to withhold or discontinue theapplication of resources to a patient that is determined to beuntreatable consistent with standards of medical ethics.

In yet another embodiment of the present invention, a patient is scoredcontinuously based on patient assessment data that is accessed by thecontinued care software 420. A scoring algorithm or a collection ofalgorithms are applied to updated assessment data to determine whetherthe current treatment plan is viable or should be amended.

In another embodiment of the present invention, computer 405 operatesorder writing software 415, either independently or in conjunction withthe operation of continued care software 420 to order tests to completethe data required for a potential diagnosis.

According to another embodiment of the present invention, the ordersissued by order writing software 415 are consistent with the servicelevel measures established by the site assessment module 130.

FIG. 5 illustrates an order writing data flow according to an embodimentof the present invention. Referring to FIG. 5, order entry userinterface 500 allows the caregiver to order procedures and medication toassist the patients at a patient monitoring station. For example, thecaregiver can order an ECG 504. Thereafter the order is reviewed and adigital signature relating to the caregiver is supplied 506. Oncereviewed and signed off, the order is approved 507 and sent to the dataoutput system 510. Thereafter the data output system prints the order tothe printer at a patient monitoring station 516. For record keepingpurposes the order is exported in the HL7 language to the hospital datasystem 518. In addition the data output system adds an item to thedatabase that will subsequently cause a caregiver to check the ECGresults. This notification to the task list is provided to the database514. In addition, as part of the database an orders file relating to thespecific patient is also kept. The fact that an ECG has been ordered isentered in the orders file for that patient.

The order entry functionality of the present invention provides acritical service for obtaining information on the patient duringadmission, medical orders, and procedures provided to the patient duringthe ICU stay. For example:

-   Radiology: Contains all radiology performed on a particular patient.-   Radiology results: Contains the results of each radiology test    performed on the particular patient.-   Drugs: Contains all relevant information for all the drugs that a    patient has been administered.-   Laboratory: Contains all laboratory tests ordered for a patient.-   Microbiology result: Contains the results of microbiology organisms    taken on a patient.-   Laboratory result: Contains the results for a laboratory test    ordered for a particular patient.

In a similar fashion using the order entry user interface 500 thecaregiver can order medications 502 for a patient.

According to an embodiment of the present invention, the order entryinterface 500 uses an identification algorithm to facilitate orderentry. As text is entered into the interface, suggested entry values areprovided to the user for selection, thereby reducing the entry time andthe opportunity of mistakes.

The medication order then is provided to an order checking system 508.The order checking system retrieves information from the database 514relating to allergies of the patient and medication list that comprisesmedications that are already being administered to the patient. Thisallows for the order checking system to check for drug allergies anddrug interactions. Further laboratory data is extracted from thedatabase 514 and the order checking system checks to insure that therewill be no adverse impact of the recommended dosage upon the renalfunction of the patient. Additionally, a patient with kidney and/orliver problems may have the dosage adjusted based on the slowerexcretion time for such patients. Once the order checking system 508 iscompleted, the order is approved and provided to the order review andsignature module 506. In this module the digital signature of acaregiver is affixed to the order electronically and the order isapproved 507. Thereafter it is provided to the data output system 510where again the orders are printed or transmitted via HL7 for thepatient monitoring station 516, for the pharmacy 517 and for thetreatment facility data system 518. In this case, any medications thatare ordered are then provided to the medications list file in thedatabase 514 so that the complete list of all medications that are beingadministered to the patient is current.

In an embodiment of the present invention, order checking system 508determines whether the order is consistent with the service levelmeasures established by the site assessment module 130. If the order isnot consistent with the service level measures, the order is suppressedand the caregiver is notified that an alternative treatment is required.

As noted, the order writing software 415 may also interact withcontinued care software 410. Referring again to FIG. 4, a caregiverselects a suggested diagnosis from the continued care software 420 andenters the order writing software 415. As previously described, theorders issued by order writing software 415 are consistent with theservice level measures established by the site assessment module 130.The order writing software identifies the appropriate test or tests andissues the actual order or orders for the identified tests. Each orderis then sent to the appropriate testing facility. The tests areconducted, and the completion of the order is reported to the data store425 and the completion information is received by the order writingsoftware 415. Additionally, continued care software 420 acquires thetest results from the datastore 425 and updates the list of suggesteddiagnoses.

Continued care software 420 provides reference material directed to thestandardized treatment of the monitored patient. In order to standardizetreatment provided to monitored patients at the highest possible level,decision support algorithms are used in the present invention. Theseinclude textural material describing the topic, scientific treatmentsand possible complications. This information is available in real timeto assist in all types of clinical decisions from diagnosis to treatmentto triage.

In an embodiment of the present invention, the decision responsealgorithms are responsive to the service level measures established bythe site assessment module 130. In this embodiment, the algorithmsadjust the response to fit the capabilities of the healthcare location.

As noted earlier, an aspect of the present invention is to standardizecare and treatment across patient monitoring stations. This is effectivein the present invention by providing decision support to caregivers aswell as information concerning the latest care and practice standardsfor any given condition. Table 1 below is an exemplary list of a widevariety of conditions within the general categories of cardiovascular,endocrinology, general, gastrointestinal, hematology, infectiousdiseases, neurology, pharmacology, pulmonary, renal, surgery,toxicology, for which algorithms of care have been developed. As will beappreciated by those skilled in the art, the list in Table 1 is notexhaustive and other decision support algorithms may be developed forother conditions without departing from the scope of the presentinvention.

TABLE 1 Bradyarrhythmias diagnosis & treatment Cardiogenic shocktreatment Cardio-pulmonary resuscitation treatment Congestive heartfailure diagnosis & treatment Emergency cardiac pacing indications Fluidresuscitation indications & treatment Hypertensive crisis treatmentImplantable cardio-defibrillators indications Intra-aortic balloondevices indications Magnesium treatment Treatment of hypotensionMyocardial infarction diagnosis & treatment MI with left bundle branchblock diagnosis Pulmonary artery catheter indications Permanentpacemakers indications Pulmonary embolism diagnosis Pulmonary embolismtreatment Supra-ventricular tachyarrhythmias diagnosis & treatmentsUnstable angina diagnosis & treatment Venous thromboembolism prophylaxistreatment Venous thrombosis: diagnosis & treatment Ventriculararrhythmias diagnosis & treatment Adrenal insufficiency diagnosis andtreatment Diabetic ketoacidosis diagnosis and treatment Hypercalcemia:diagnosis & treatment Hyperglycemia: insulin treatment Steroidreplacement treatment Thyroid disease diagnosis and treatment End oflife treatment decisions Pressure ulcers treatment Organ procurementindications Antibiotic associated colitis diagnosis and treatmentHepatic encephalopathy diagnosis and treatment Hepatic failure diagnosisand treatment Treatment of patients with ascites Nutritional managementAcute pancreatitis diagnosis and treatment Upper gastro-intestinalbleeding: stress prophylaxis treatment Upper gastro-intestinal bleeding:non-variceal treatment Upper gastro-intestinal bleeding: varicealtreatment Heparin treatment Heparin-induced thrombocytopenia diagnosisand treatment The bleeding patient diagnosis and treatmentThrombocytopenia diagnosis and treatment Thrombolytic treatmentTransfusion indications Hematopoetic growth factor indications Warfarintreatment Acalculus cholecystitis diagnosis and treatment Bloodstreaminfections diagnosis and treatment Candiduria diagnosis and treatmentCatheter related septicemia diagnosis and treatment Catheter replacementstrategies Endocarditis prophylaxis Endocarditis diagnosis and treatmentFebrile neutropenia diagnosis and treatment Fever of Unknown Origindiagnosis HIV+ patient infections diagnosis and treatment Meningitisdiagnosis and treatment Necrotizing soft tissue infections diagnosis andtreatment Non-infectious causes of fever diagnosis Ophthalmic infectionsdiagnosis and treatment Pneumonia, community acquired diagnosis andtreatment Pneumonia, hospital acquired diagnosis and treatment Septicshock diagnosis and treatment Sinusitis diagnosis and treatment SystemicInflammatory Response Syndrome diagnosis and treatment Transplantinfection prophylaxis Transplant-related infections diagnosis andtreatment Agitation, anxiety, depression & withdrawal treatment Braindeath diagnosis Guillain-barre syndrome diagnosis and treatmentIntracerebral hemorrhage diagnosis and treatment Myasthenia gravisdiagnosis and treatment Neuromuscular complications of critical illnessdiagnosis and treatment Non-traumatic coma diagnosis Sedation treatmentStatus epilepticus diagnosis and treatment Stroke diagnosis andtreatment Sub-arachnoid hemorrhage diagnosis and treatmentAminoglycoside dosing and therapeutic monitoring Amphotericin-btreatment Analgesia treatment Drug changes with renal dysfunctionPenicillin allergy diagnosis and treatment Neuromuscular blockertreatment Vancomycin treatment Adult Respiratory Distress Syndrome:hemodynamic treatment Adult Respiratory Distress Syndrome: steroidtreatment Adult Respiratory Distress Syndrome: ventilator treatmentAsthma diagnosis & treatment Bronchodilator use in ventilator patientsBronchoscopy & thoracentesis indications Chronic Obstructive PulmonaryDisease treatment Chest X-ray indications Noninvasive modes ofventilation indications Endotracheal tubes & tracheotomy indicationsTreatment of airway obstruction Ventilator weaning Acute renal failure:diagnosis and treatment Dialysis indications Diuretic treatmentHyperkalemia: diagnosis & treatment Hypernatremia: diagnosis & treatmentHypokalemia: diagnosis & treatment Hyponatremia: diagnosis & treatmentOliguria diagnosis and treatment Obstetrical complications and treatmentDissecting aortic aneurysm diagnosis and treatment Post-operativehypertension treatment Post-operative myocardial ischemia (non-cardiacsurgery) treatment Diagnosis and treatment of arrhythmias after cardiacsurgery Diagnosis and treatment of post-operative bleedingPost-operative management of abdominal Post-operative management of openheart Post-operative management of thoracotomy Post-operative managementof carotid Wound healing treatment Diagnosis and treatment ofacetaminophen overdose Diagnosis and treatment of anaphylaxis Diagnosisand treatment of cocaine toxicity Diagnosis and treatment of alcoholwithdrawal Diagnosis and treatment of hyperthermia Diagnosis andtreatment of latex allergy Diagnosis and treatment of unknown poisoningDiagnosis and treatment of abdominal compartment syndrome Diagnosis andtreatment of blunt abdominal injury Diagnosis and treatment of bluntaortic injury Diagnosis and treatment of blunt cardiac injury DeepVenous Thrombosis prophylaxis treatments Acid-base disturbance diagnosisand treatment Electrolyte disturbance diagnosis and treatment Severityadjustment calculation and outcome prediction Ventilator treatmentContinuous renal replacement treatment Infusion pump administrationtreatment Fungal infection diagnosis and treatment Viral infectiondiagnosis and treatment Diagnosis and treatment of extremity compartmentsyndrome Diagnosis and treatment of head injury Diagnosis and treatmentof hypothermia Diagnosis and treatment of identification of cervicalcord injury Diagnosis and treatment of spinal cord injury Diagnosis andtreatment of open fractures Diagnosis and treatment of penetratingabdominal injury Diagnosis and treatment of penetrating chest injuryAdmission criteria Discharge criteria Patient triage Discharge planning

FIGS. 6A, B, C and 6D illustrate an application of a decision supportalgorithm for the diagnosis and treatment of acalculous cholecystitis topatient data according to an embodiment of the present invention. FIGS.6A through 6D are exemplary only and are not limiting. As will beappreciated by those skilled in the art, decision support algorithms(DSAs) for other conditions may be implemented in the continued caresoftware without departing from the scope of the present invention.

Referring to FIG. 6A, a datastore comprising patient data is accessed bythe DSA 600 for data indicative of clinical infection. A determinationis made whether the data is sufficient to determine whether the patientis clinically infected 602. If the data necessary to make the decisionare not available, the system continues its monitoring 604 until data inthe datastore indicates otherwise. Alternatively, an alert may be issuedon a monitor at the command center although this is not a requirementfor further tests to be ordered. Test that are ordered by the DSA arethen performed on the patient to obtain the data required for thedecision.

If the data are sufficient, a determination is made whether the patientmeets criteria for a clinical infection as measured by elevatedtemperature and leukocystosis 606. In an embodiment of the presentinvention, the criteria are temperature great than 102 F., or a whiteblood cell count greater than 12,000. If the criteria for clinicalinfection are not met the system of the present invention goes back intoits continuous monitoring mode 608. The process is then complete and thecontinuous monitoring of the present invention continues.

If the patient is clinically infected 606, the DSA accesses the patientdata datastore and acquires data indicative of whether the patient hashad a previous cholecystectomy 610. A determination is then made whetherthe data is sufficient to determine whether the patient has had aprevious cholecsystectomy 612. If the data necessary to make thedecision are not available, the DSA prompts the caregiver to find outthis information 613. When the information is obtained it is put intothe datastore. Notations of “incomplete data” are kept by the system sothat treatment records and need for tests can be audited. This isaccomplished by storing an “incomplete data” record 614.

If the data are sufficient, a determination is made whether the patienthas had a previous cholecystectomy 616. If the patient has had aprevious cholecystectomy, it is very unlikely that the patient hasacalculous cholecystitis. Therefore the DSA has completed its analysisfor acalculous cholecytitis and the continuous monitoring of the presentinvention continues for other possible etiologies of infection 618.

Referring to FIG. 6B, if the patient has not had a previouscholecystectomy, the DSA accesses the patient datastore and acquiresdata indicative of whether the patient has any of a set of risk factors620. In another embodiment of the present invention, the risk factorscomprise: 1) Prolonged intensive care unit (ICU) stay (defined asgreater than six (6) days); 2) recent surgery within the last two weeks(particularly aortic cross clamp procedures); 3) hypotension (BP lessthan 90 mmHg); 4) positive end-expiratory pressure (PEEP) greater thanten (10) centimeters (cm); 5) transfusion greater than six (6) units ofblood; 6) inability to use the gastrointestinal (GI) tract fornutrition; or 7) immunosuppresssion (AIDS, transplantation, orleukemia).

If the data are sufficient, a determination is made whether the patienthas any of the risk factors 626. If the patient does not have any of therisk factors, the diagnostic process is then complete and the continuousmonitoring of the present invention continues 628.

If the patient has any of the seven risk factors, the DSA accesses thepatient data datastore and acquires data indicative of whether thepatient has any of a set of symptoms 630 or abnormal laboratory values.A determination is made whether the data is sufficient to determinewhether the patient has any of the symptoms 632 or abnormal laboratoryvalues. If the data necessary to make the decision are not available,the DSA directs the order writing software 415 (see FIG. 4) to order thetests 633. Results are sent to the datastore. Notations of “incompletedata” are kept by the system so that treatment records and need fortests can be audited. This is accomplished by storing an “incompletedata” record 634. Alternatively, an alert may be issued on a monitor atthe command center to check for right upper quadrant tenderness althoughthis is not a requirement for further tests to be ordered. In anotherembodiment of the present invention, the symptoms comprise: right upperquadrant (RUQ) tenderness and the abnormal laboratory results comprisingelevated alkaline phosphatase; elevated bilirubin; or elevated livertransaminases.

If the data are sufficient, a determination is made whether the patienthas any of the symptoms 636 or abnormal laboratory values. If thepatient does not have any of the symptoms or abnormal laboratory values,the DSA concludes that it is very unlikely that the patient hasacalculous cholecystitis. The process is then complete and thecontinuous monitoring of the present invention continues 638.

Referring to FIG. 6C, if the patient has any of the symptoms or abnormallaboratory values, the DSA accesses the patient data datastore andacquires data indicative of whether alternative intra-abdominalinfectious sources are more likely 640. A determination is made whetherthe data is sufficient to determine whether the other infectious sourcesare more likely 642. If the data necessary to make the decision are notavailable, the DSA prompts the user for a response as to whether otherinfectious causes are present and considered more likely 644. The usercan then provide the requested information that can be considered by thesystem 646 for further analysis.

If the data are sufficient, a determination is made whether othersources of infection are more likely 646. Regardless of the outcome ofthis determination, the DSA accesses the patient datastore and acquiresdata indicative of whether the patient is sufficiently stable to besubjected to testing outside of the critical care environment 650. Adetermination is made whether the data are sufficient to determinewhether the patient is stable to go outside of the critical careenvironment 652. If the data necessary to make the decision are notavailable, the DSA prompts the user for a response 654 and may directthe order writing software 415 (see FIG. 4) to order tests or procedures653 that will assist in such a determination. An “incomplete data”record is also created 651. Test results are sent to the datastore.Notations of “incomplete data” are kept by the system so that treatmentrecords and need for tests can be audited. This is accomplished bystoring an “incomplete data” record 654. Alternatively, an alert may beissued on a monitor at the command center although this is not arequirement for further tests to be ordered.

Referring to FIG. 6D, if the data are sufficient, a determination ismade whether the patient is sufficiently stable to be subjected totesting outside of the critical care environment 656.

If the patient is not sufficiently stable to be subjected to testingoutside of the critical care environment (regardless of whether othersources of infection are indicated), the DSA issues a message comprisinga recommendation that empiric antibiotic be considered and a bedsideultrasound be performed and the results communicated to the patientdatastore 658. In still another embodiment of the present invention, theDSA directs the order writing software (see FIG. 4) to order the bedsideultrasound. The DSA accesses the test results and other patient data662. If no other infectious etiologies are identified, no abnormalitiesof the gall-bladder are noted, and the patient is not improving, the DSAissues a message comprising a “provisional diagnosis of acalculouscholecystitis” and recommends an empiric cholecystectomy and systemicantibiotics 664. If no other infectious etiologies are identified, noabnormalities of the gall bladder are noted, and the patient isimproving, the DSA issues a message comprising a recommendation toobserve the patient 666.

If the patient is sufficiently stable to go outside of the critical careenvironment for a test and a determination was made that no othersources of infection were indicated (see FIG. 6C, 646), the DSA issuesan order that empiric antibiotics be considered and a morphine sulfateCholescintigraphy test be performed 668 and the results communicated tothe datastore. In still another embodiment of the present invention, theDSA directs the order writing software 415 (see FIG. 4) to order thetest.

A determination is made whether the results of the tests are normal 670.If the test indicates an abnormality, the DSA issues a messagecomprising a recommendation to consider a diagnosis of acalculouscholecystitis, administer systemic antibiotics and perform either acholecystectomy or a percutaneous drainage 672. If the results arenormal, acalculous cholecystitis is excluded 674. The process is thencomplete and the continuous monitoring of the present inventioncontinues.

If the patient is sufficiently stable to go outside of the critical careenvironment for a test and a determination was made that other sourcesof infection were indicated (see FIG. 6C, 646), the DSA issues an orderto consider empiric antibiotics and for an abdominal CT scan to beperformed 680 and the results communicated to the datastore. In stillanother embodiment of the present invention, the DSA directs the orderwriting software 415 (see FIG. 4) to order the test.

The test results and other data are analyzed 682 and a determination ismade whether other infection sources are indicated and whether the gallbladder is normal or if abnormalities are present that are notdiagnostic 684. If other infectious etiologies are not apparent and thetest: a) demonstrates abnormalities of the gall bladder but notdiagnostic; or b) no gall-bladder abnormalities are noted, the DSAissues a report comprising a recommendation to maintain continuedobservation of the patient 686. The process is then complete and thecontinuous monitoring of the present invention continues. Alternatively,if other infectious etiologies are apparent, the DSA will makerecommendations as to further diagnostics and treatments.

While the decision support algorithm described with reference to FIGS.6A, B, C and 6D refers to a continuous monitoring “mode” of the presentinvention, this is not meant as a limitation. As previously described,embodiments of the present invention anticipate environments in whichdata is stored and evaluated on a “delayed” basis. The decision supportalgorithms described with reference to FIGS. 6A, B, C and 6D may beadapted to operate with delayed data Without departing from the scope ofthe present invention.

Referring again to FIGS. 1 and 2, the remote command center comprises anA/V conferencing server 190. In an embodiment of the present invention,A/V conferencing server 190 acquires audio and video signals frompatient monitoring station “A” and provides a terminal (not shown)access to these signals via external network access 195. In yet anotherembodiment of the present invention addition, a local terminal (notshown) operated by a “local visitation participant” or “LVP” and aremote terminal (not shown) operated by a “remote visitationparticipant” or “RVP” are bridged by A/V conferencing server 190 toprovide audio and video signals from the patient monitoring station, thelocal terminal and the remote terminal available simultaneously to LVPand RVP. Additionally, a terminal user may control the position ofcamera 205. By way of illustration and not as a limitation, RVPs may befamily members or other concerned parties while LVPs may be patients,nurses, doctors, family members or other concerned parties. Thisembodiment thus permits family members the capability to “virtuallyvisit” other sick family members when a physical visit to a patient'slocation is not possible and/or desirable. The “virtual visit” furtherallows the possibility to see and speak with a care provider regarding apatient's care or related subjects without having to be physicallylocated at the health care provider's location. The present inventionalso provides a means for the floor staff (i.e. those caregivers in thehospital at or near the patient's bedside) to instantly alert thecommand center of the conditions of patients who destabilize therebyallowing for more rapid response by those manning the command center.

When each command center person logs onto the system of the presentinvention, a background service is started. This service subscribes toan emergency alert server that is connected to a video server. As notedearlier, the video server provides video feed from each beside to thecommand center as needed. Emergency message are passed from the bedsidethrough the video server to the command center. As the emergency alertserver receives a message from a video server, it sends a message to allof the subscribed services in the command center. This notificationalerts the command center users by means of a “pop-up” alert window atthe users' workstation that an emergency condition exists at the bedcalling for the alert, and that the floor caregiver has requestedimmediate backup.

To facilitate the emergency call capability of the present invention, inaddition to the various network connections of a more automated type, anemergency “call button” is provided at each critical care location. Thiscould by or near each bed, at a nurse's station, at a mobile care bed orany location where the patient may be located. When pressed, the callbutton causes a message to be sent to the emergency alert server at thecommand center that a patient emergency has occurred.

The present invention comprises a video/audio server (Axis 2401)dedicated to each critical care location. A button activation mechanismand associated wiring is provided to allow the call button to bepositioned in the room at a location convenient to the caregiver callingfor command center backup.

Currently each video server can support up to 16 call buttons by usingcombinations of the four inputs to signify one alarm in a 4-bit binarypattern although this is not meant as a limitation. A typicalinstallation would use one button or perhaps two (e.g. two beds perroom) per video server.

A software interrupt event handler is configured on the video server torespond to activation of the emergency call button.

The emergency alert server comprises a web service called for sendingemergency alert signals that is placed in service at system startup.When called, emergency alert web service responds with anacknowledgement message (e.g. “Alert Received”). The emergency alert webservice identifies the ward and bed directly from the IP address (uniqueto each video server) and input number it was passed. It then sends amessage to all subscribing clients identifying the emergency condition,the ward, and bed.

When a user logs into a workstation at the command center a user alertservice subscribes to the emergency alert server and waits for anyemergency message in the background. Upon receiving an emergencymessage, the service will popup a window with the message on top of thedesktop and stay there until the user dismisses or acknowledges thealert. The user alert service the loads video assessment module to allowthe command center to view the bed with the emergency.

In another embodiment of the present invention, a critical care hospitalbed comprises monitoring instruments linked to a wireless network. Thisserves the needs of those patients who are transported from one locationto another (either internal to a hospital or to other hospitals ordiagnostic centers) for testing, procedures or other reasons. In thisembodiment, monitoring continues using typical monitoring means thathave been described above which include, without limitation,physiological monitoring equipment, video monitoring equipment and anemergency call button, all of which transmit their signals in a wirelessfashion so that movement of the patient bed does not interrupt thetransmission of information.

A telecommunications network for remote patient monitoring has now beenillustrated. It will be apparent to those skilled in the art that othervariations of the present invention are possible without departing fromthe scope of the invention as disclosed. For example, one can envisiondifferent ratios of remote command center to patient monitoringstations. Certain types of decision support algorithms would be used byintensivists, other types of remote monitoring of not only patientmonitoring stations but other types of hospital functions as well asindustrial functions where critical expertise is in limited supply butwhere that expertise must be applied to ongoing processes. In such casesa system such as that described can be employed to monitor processes andto provide standardized interventions across a number of locations andoperations. Further, any reference to claim elements in the singular,for example, using the articles “a,” “an,” or “the” is not to beconstrued as limiting the element to the singular.

1. An order evaluation system comprising: a network; a datastoreaccessible to a remote command center via the network, wherein thedatastore comprises assessment data elements indicative of medicalconditions associated with geographically dispersed patients; a decisionsupport system at the remote command center, wherein the decisionsupport system is connected to the network, wherein the decision supportsystem comprises an order checking module, and wherein the orderchecking module comprises instructions for: receiving an orderassociated with a patient; evaluating the order using a first set ofselected assessment data elements associated with the patient;challenging the order if the order is contraindicated by the first setof selected assessment data elements; and sending the order to an orderwriting module if the order is indicated by the first set of selectedassessment data elements; a rules generator connect to the network,wherein the rules generator comprises instructions for establishing apatient-specific rule for the patient consistent with the order; and arules engine at the remote command center, wherein the rules engine isconnected to the network and comprises instructions for: applying thepatient-specific rule continuously to a second set of selectedassessment data elements associated with the patient; determining in anautomated fashion 24 hours per day 7 days per week whether thepatient-specific rule for the patient has been contravened; and issuingan alert if the patient-specific rule for the patient has beencontravened.
 2. The order evaluation system of claim 1, wherein thepatient is at a location that is remote from the command center.
 3. Theorder evaluation system of claim 1, wherein the order is an order formedication and wherein the first set of selected assessment data isselected from the group consisting patient data, medication data,clinical data, monitored data, physiological data, and symptomatic data.4. The order evaluation system of claim 3, wherein the medication datacomprises current medications and drug allergy information.
 5. The orderevaluation system of claim 4, wherein the physiological data comprisesdata indicative of liver function and renal function.
 6. The orderevaluation system of claim 1, wherein the patient-specific rule for thepatient comprises an algorithm.
 7. The order evaluation system of claim1, wherein the second set of selected assessment data elements comprisesa physiological data element of the patient and a clinical data elementof the patient.
 8. The order evaluation system of claim 1, wherein thesecond set of selected assessment data elements comprises aphysiological data element of the patient and a medication data elementof the patient.
 9. The order evaluation system of claim 1, wherein thesecond set of selected assessment data elements comprises aphysiological data element of the patient and a laboratory data elementof the patient.
 10. The order evaluation system of claim 1, wherein thesecond set of selected assessment data elements comprises a clinicaldata element of the patient and a laboratory data element of thepatient.
 11. The order evaluation system of claim 1, wherein the secondset of selected assessment data elements comprises a physiological dataelement of the patient and another physiological data element of thepatient.
 12. The order evaluation system of claim 1, wherein the secondset of selected assessment data elements comprises at least two dataelements of the patient selected from the group consisting of aphysiological data element, a clinical data element of the patient, amedication data element of the patient, and a laboratory data element ofthe patient.
 13. The order evaluation system of claim 1, wherein theremote command center comprises: an external network interface, whereinthe external network interface comprises instructions for connecting toan external network; and instructions for providing a health careprovider access to the remote command center via the external network.14. The order evaluation system of claim 13, wherein the externalnetwork is selected from the group consisting of a wired network, awireless network, a cable network, a fiber optic network, and theInternet.
 15. The order evaluation system of claim 13, wherein thehealth care provider is selected from the group consisting of aphysician, a nurse, a clinician, a diagnostician, and a intensivist. 16.The order evaluation system of claim 13, wherein the remote commandcenter further comprises instructions for sending the health careprovider the alert if the patient-specific rule for the hospitalizedpatient has been contravened.
 17. A method for evaluating orderscomprising: storing assessment data elements indicative of a medicalconditions associated with geographically dispersed patients in adatastore, wherein the datastore is accessible to a remote commandcenter via a network; receiving an order relating to a patient;accessing assessment data elements indicative of a medical conditionassociated with the patient from the remote command center; evaluatingthe order using a first set of selected assessment data elementsassociated with the patient; challenging the order if the order iscontraindicated by the first set of selected assessment data elements;and sending the order to an order writing module if the order isindicated by the first set of selected assessment data elements;establishing a patient-specific rule for the patient consistent with theorder; applying the patient specific rule continuously to a second setof selected assessment data elements associated with the patient;determining in an automated fashion 24 hours per day 7 days per week atthe remote command center whether the patient-specific rule for thepatient has been contravened; and issuing an alert if thepatient-specific rule for the patient has been contravened.
 18. Themethod for evaluating orders of claim 17, wherein the patient is at alocation that is remote from the command center.
 19. The method forevaluating orders of claim 17, wherein the order is an order formedication and wherein the first set of selected assessment data isselected from the group consisting patient data, medication data,clinical data, monitored data, physiological data, and symptomatic data.20. The method for evaluating orders of claim 19, wherein the medicationdata comprises current medications and drug allergy information.
 21. Themethod for evaluating orders of claim 20, wherein the physiological datacomprises data indicative of liver function and renal function.
 22. Themethod for evaluating orders of claim 17, wherein the patient-specificrule for the patient comprises an algorithm.
 23. The method forevaluating orders of claim 17, wherein the second set of selectedassessment data elements comprises a physiological data element of thepatient and a clinical data element of the patient.
 24. The method forevaluating orders of claim 17, wherein the second set of selectedassessment data elements comprises a physiological data element of thepatient and a medication data element of the patient.
 25. The method forevaluating orders of claim 17, wherein the second set of selectedassessment data elements comprises a physiological data element of thepatient and a laboratory data element of the patient.
 26. The method forevaluating orders of claim 17, wherein the second set of selectedassessment data elements comprises a clinical data element of thepatient and a laboratory data element of the patient.
 27. The method forevaluating orders of claim 17, wherein the second set of selectedassessment data elements comprises a physiological data element of thepatient and another physiological data element of the patient.
 28. Themethod for evaluating orders of claim 17, wherein the second set ofselected assessment data elements comprises at least two data elementsof the patient selected from the group consisting of a physiologicaldata element, a clinical data element of the patient, a medication dataelement of the patient, and a laboratory data element of the patient.29. The method of evaluating orders of claim 17 further comprising:interfacing with an external network; and providing a health careprovider access to the remote command center via the external network.30. The method of evaluating orders of claim 29, wherein the externalnetwork is selected from the group consisting of a wired network, awireless network, a cable network, a fiber optic network, and theInternet.
 31. The method of evaluating orders of claim 29, wherein thehealth care provider is selected from the group consisting of aphysician, a nurse, a clinician, a diagnostician, and a intensivist. 32.The method of evaluating orders of claim 29 further comprising sendingthe health care provider the alert if the patient-specific rule for thehospitalized patient has been contravened.